Markovian Coupling vs. Conductance for the Jerrum-Sinclair Chain

We show that no Markovian Coupling argument can prove rapid mixing of the Jerrum-Sinclair Markov chain for sampling almost uniformly from the set of perfect and near perfect matchings of a given graph. In particular, we show that there exists a bipartite graph G such that any Markovian coupling argument on the Jerrum-Sinclair Markov chain for G must necessarily take time exponential in the number of vertices in G. This holds even when the coupling argument is Time-Variant, i.e., the transition probabilities used by the coupling process depend upon the history of the process. In contrast, the above Markov chain on G has been shown to mix in polynomial time using conductance arguments.

• Type: Conference
• Year: 1999
• Where: FOCS
• Authors: V. S. Anil Kumar, H. Ramesh
• Keywords: Coupling Process Depend, FOCS 1999, Jerrum-Sinclair Markov Chain, Markovian Coupling Argument, Theoretical Computer Science